In the forward-looking infrared (FLIR) imaging of a non-uniform scene such as terrain, point targets whose temperature is substantially higher or lower than that of the background (e.g. aircraft of long range) are often not detected by the target detection algorithms conventionally used in FLIR imaging. Conventional target detection algorithms can also falsely mark many background clutter features as targets. Such target detection algorithms include leading-edge-trailing-edge detection and least-mean-squared (LMS) filtering. One-dimensional LMS filters can produce false target indications on edges of background objects, as is the case for leading-edge-trailing-edge detection, and even the use of two orthogonal one-dimensional LMS filters can still produce false target indications on corners. In order to isolate point targets for a clear display, it is necessary to determine the spatial extent and spatial connections of an object of interest in real time--a difficult computational feat.
Prior art in this field includes: U.S Pat. No. 4,742,557 to Ma, which shows a system for extracting character information from a noisy background in an optical scanner; U.S. Pat. No. 4,736,439 to May, which relates to the preprocessing of an image by median subtraction; and U.S. Pat. No. 4,685,143 to Choate, which deals with a scheme for analyzing edge spectra.